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358 results for “fine-scale”
Data from: Fine-scale genetic structure in the orchid Gymnadenia conopsea is not associated with local density of flowering plants
<p><span><strong>Premise</strong>:</span><span> Density-dependent pollinator visitation can lead to density-dependent mating patterns and within-population genetic structure. In Gymnadenia conopsea, individuals in low-density patches receive more self-pollen than individuals in high-density patches, suggesting higher relatedness at low density. Ongoing fragmentation is also expected to cause more local matings, potentially leading to biparental inbreeding depression.</span></p> <p><span><strong>Methods</strong>: </span><span>To evaluate whether relatedness decreases with local density, we analysed 1315 SNP loci in 113 individuals within two large populations. We quantified within-population genetic structure in one of the populations, recorded potential habitat barriers, and visualized gene flow using estimated effective migration surfaces (EEMS). We further estimated the magnitude of biparental inbreeding depression that would result from matings restricted to within 5 m.</span></p> <p><span><strong>Results</strong>: </span><span>There was no significant relationship between local density and relatedness in any population. We detected significant fine-scale genetic structure consistent with isolation-by-distance, with positive kinship coefficients at distances below 10 m. Kinship coefficients were low, and predicted biparental inbreeding depression resulting from matings within the closest 5 m was a modest 1–3%.</span> <span>EEMS suggested that rocks and bushes may act as barriers to gene flow within a population.</span></p> <p><span><strong>Conclusions</strong>: </span><span>The results suggest that increased self-pollen deposition in sparse patches does not necessarily cause higher selfing rates, or that inbreeding depression results in low establishment success of inbred individuals. The modest relatedness suggests that biparental inbreeding depression is unlikely to be an immediate problem following fragmentation of large populations. The results further indicate that habitat structure may contribute to governing fine-scale genetic structure in <em>G. conopsea</em>.</span></p>
Regional and fine-scale local adaptation in salinity tolerance in Daphnia inhabiting contrasting clusters of inland saline waters
<p>Freshwater salinisation is an important threat to biodiversity, ecosystem functioning, and the provision of ecosystem services. Therefore, understanding the capacity of species to adapt to salinity gradients is crucial. Clusters of naturally saline habitats represent ideal test cases to study the extent and scale of local adaptation to salinisation. We studied local genetic adaptation of the water flea Daphnia magna, a key component of pond food webs, to salinity in two contrasting landscapes - a dense cluster of sodic bomb crater ponds and a larger-scale cluster of soda pans. We show regional differentiation in salinity tolerance reflecting the higher salinity levels of soda pans versus bomb crater ponds. We found local adaptation to differences in salinity levels at the scale of tens of metres among bomb crater pond populations but not among geographically more distant soda pan populations. The population-level salinity tolerance range was reduced in more saline bomb crater ponds through an upward shift of the minimum salt tolerance observed across clones and a consequent gradual loss of less tolerant clones in a nested pattern. Our results show genetic adaptation to salinity gradients at different spatial scales and fine-tuned local adaptation in neighbouring habitat patches in a natural landscape.</p>
RBE-DS-NO2: A fine-scale NO2 dataset during 2005-2020 in China
<p><span> </span><span>RBE-DS-NO2 is a long-term, high-resolution NO<sub>2</sub> dataset for China. This dataset was generated by employing the robust back-extrapolation via a data augmentation approach (RBE-DA) to ensure the predictive accuracy in back-extrapolation before 2013, and by utilizing an improved spatial downscaling technique (DS) to refine the spatial resolution from 10 km to 1 km. Back-extrapolation validation based on 2005-2012 observations from sites in Taiwan province yielded an<em> R<sup>2</sup></em> of 0.72 and RMSE of 10.7 μg/m<sup>3</sup>, while cross-validation across China during 2013-2020 showed an <em>R<sup>2</sup></em> of 0.73 and RMSE of 9.6 μg/m<sup>3</sup>. </span></p>
Trophic resource partitioning drives fine-scale coexistence in cryptic bat species
Understanding the processes that enable species coexistence has important implications for assessing how ecological systems will respond to global change. Morphology and functional similarity increase the potential for competition, and therefore, co-occurring morphologically similar but genetically unique species are a good model system for testing coexistence mechanisms. We used DNA metabarcoding and High Throughput Sequencing to characterise for the first time the trophic ecology of two recently-described cryptic bat species with parapatric ranges, Myotis escalerai and Myotis crypticus. We collected faecal samples from allopatric and sympatric regions and from syntopic and allotopic locations within the sympatric region to describe the diets both taxonomically and functionally and compare prey consumption with prey availability. The two bat species had highly similar diets characterised by high arthropod diversity, particularly Lepidoptera, Diptera and Araneae, and a high proportion of prey that is not volant at night, which points to extensive use of gleaning. Diet overlap at the prey-item level was lower in syntopic populations, supporting trophic shift under fine-scale co-occurrence. Furthermore, the diet of M. escalerai had a marginally lower proportion of not nocturnally volant prey in syntopic populations, suggesting that the shift in diet may be driven by a change in foraging mode. Our findings suggest that fine-scale coexistence mechanisms can have implications for maintaining broad-scale diversity patterns. This study highlights the importance of including both allopatric and sympatric populations and choosing meaningful spatial scales for detecting ecological patterns. We conclude that a combination of high taxonomic resolution with a functional approach helps identify patterns of niche shift.
Fine-scale spatial patterns of wildlife disease are common and understudied
<p>1. All parasites are heterogeneous in space, yet little is known about the prevalence and scale of this spatial variation, particularly in wild animal systems. To address this question, we sought to identify and examine spatial dependence of wildlife disease across a wide range of systems.</p> <p>2. Conducting a broad literature search, we collated 31 such datasets featuring 89 replicates and 71 unique host-parasite combinations, only 51% of which had previously been used to test spatial hypotheses. We analysed these datasets for spatial dependence within a standardised modelling framework using Bayesian linear models, and we then meta-analysed the results to identify generalised determinants of the scale and magnitude of spatial autocorrelation.</p> <p>3. We detected spatial autocorrelation in 48/89 model replicates (54%) across 21/31 datasets (68%), spread across parasites of all groups. Even some very small study areas (under 0.01km2) exhibited substantial spatial variation.</p> <p>4. Despite the common manifestation of spatial variation, our meta-analysis was unable to identify host-, parasite-, or sampling-level determinants of this heterogeneity across systems. Parasites of all transmission modes had easily detectable spatial patterns, implying that structured contact networks and susceptibility effects are potentially as important in spatially structuring disease as are environmental drivers of transmission efficiency.</p> <p>5. Our findings demonstrate that fine-scale spatial patterns of infection manifest frequently and across a range of wild animal systems, and many studies are able to investigate them – whether or not the original aim of the study was to examine spatially varying processes. Given the widespread nature of these findings, studies should more frequently record and analyse spatial data, facilitating development and testing of spatial hypotheses in disease ecology. Ultimately, this may pave the way for an a priori predictive framework for spatial variation in novel host-parasite systems.</p>
Fine-scale spatial segregation in a pelagic seabird driven by differential use of tidewater glacier fronts
<div class="WordSection1"> <p><span><span>In colonially breeding marine predators, individual movements and colonial segregation are influenced by seascape characteristics. Tidewater glacier fronts are important features of the Arctic seascape and are often described as foraging hotspots. Albeit their documented importance for wildlife, little is known about their structuring effect on arctic predator movements and space use. In this study, we tested the hypothesis that tidewater glacier fronts can influence marine bird foraging patterns and drive spatial segregation among adjacent colonies. We analysed movements of black-legged kittiwakes (<i>Rissa tridactyla</i>) in a glacial fjord by tracking breeding individuals from five colonies. Although breeding kittiwakes were observed to travel up to <i>ca</i>. 280 km from the colony, individuals were more likely to use glacier fronts located closer to their colony and rarely used glacier fronts located farther away than 18 km. Such variation in the use of glacier fronts created fine-scale spatial segregation among the four closest (<i>ca</i>. 7 km distance on average) kittiwake colonies. Overall, our results support the hypothesis that spatially predictable foraging patches like glacier fronts can have strong structuring effects on predator movements and can modulate the magnitude of intercolonial spatial segregation in central-place foragers.</span></span></p> </div> <p> </p>
R scripts for "Using LiDAR to assess the influence of fine-scale habitat structure on the abundance of the bearded reedling (Panurus biarmicus)"
<p>Dataset which contains R scripts and R package SDMaps used for data preparation and modelling in the methodology described in my MSc thesis "Using LiDAR to assess the influence of fine-scale habitat structure on the abundance of the bearded reedling (<em>Panurus biarmicus</em>)".</p> <p>The project involved creating Species Distribution Models to test whether and how fine-scale habitat structure - in the form of LiDAR derived variable - influences the relative abundance of the bearded reedling in the Netherlands, beyond other variables such as land use, soil type and climate data.</p> <p>These scripts can serve as an example of how the SDMaps package can be used to build Species Distribution Models that include LiDAR derived variables, and to replicate some of the methodologies described in the thesis. The SDMaps package contains an installation guide, manual, tutorial and examples.</p>
Biomass fine-scale variation is predictive of functional composition and diversity in grazed grassland
<p>Dataset and R codes used in "Biomass fine-scale variation is predictive of functional composition and diversity in grazed grassland"</p>
The importance of fine-scale predictors of wild boar habitat use in an isolated population
<p>Predicting the likelihood of wildlife presence at potential wildlife-livestock interfaces is challenging. These interfaces are usually relatively small geographical areas where landscapes show large variation over small distances. Models of wildlife distribution based on coarse data over wide geographical ranges may not be representative of these interfaces. High-resolution data can help identify fine scale predictors of wildlife habitat use at a local scale and provide more accurate predictions of species habitat use. These data may be used to inform knowledge of interface risks, such as disease transmission between wildlife and livestock, or human-wildlife conflict. This study uses fine-scale habitat use data from wild boar (Sus scrofa) based on activity signs and direct field observations in and around the Forest of Dean in Gloucestershire, England. Spatial logistic regression models fitted using a variant of penalized quasi‐likelihood were used to identify habitat-based and anthropogenic predictors of wild boar signs. Our models showed that within the Forest of Dean, wild boar signs were more likely to be seen in spring, in forest-type habitats, closer to the centre of the forest and near litter bins. In the area surrounding the Forest of Dean, wild boar signs were more likely to be seen in forest-type habitats and near recreational parks and less likely to be seen near livestock. This approach shows that wild boar habitat use can be predicted using fine-scale data over comparatively small areas and in human-dominated landscapes, whilst taking account of the spatial correlation from other nearby fine-scale data-points. The methods we use could be applied to map habitat use of other wildlife species in similar landscapes, or of movement-restricted, isolated or fragmented wildlife populations.</p>
Fine-scale spatial genetic structure in a locally abundant native bunchgrass (Achnatherum thurberianum) including distinct lineages revealed within seed transfer zones
<p>Analyses of the factors shaping genetic variation in widespread plant species are important for understanding evolutionary history and local adaptation and have applied significance for guiding conservation and restoration decisions. Thurber's needlegrass (<em>Achnatherum</em> <em>thurberianum</em>) is a widespread, locally abundant grass that inhabits heterogeneous arid environments of western North America and is of restoration significance. It is a common component of shrubland steppe communities in the Great Basin Desert, where drought, fire, and invasive grasses have degraded natural communities. Using a reduced representation sequencing approach, we generated SNP data at 5,677 loci across 246 individuals from 17 <em>A. thurberianum</em> populations spanning five previously delineated seed zones from the western Great Basin. Analyses revealed pronounced population genetic structure, with individuals forming consistent geographical clusters across a variety of population genetic analyses and spatial scales. Low levels of genetic diversity within populations, as well as high population estimates of linkage disequilibrium and relatedness, were consistent with self-fertilization as a contributor to population differentiation. Variance partitioning and partial redundancy analysis (pRDA) indicated local adaptation to environment as additionally influencing the spatial distribution of genetic variation. The environmental variables driving these results were similar to those implicated in recent genecological work which inferred local adaptation for seed zone delineation. Our analyses also revealed a complex evolutionary history of <em>A. thurberianum</em> in the Great Basin, where previously delineated seed zones contain distantly related populations. Our results indicate evolutionary history, mating system, and differentiation across distinct geographic and environmental scales have shaped genetic variation in <em>A. thurberianum</em> and illustrate how numerous aspects of population genetic variation might require consideration for restoration planning.</p>
Integrative species delimitation reveals fine-scale allopatric speciation in a good-flying insect: A case study on Cylindera pseudocylindriformis complex (Coleoptera, Cicindelidae)
<p>Alpha taxonomy is fundamental for many biological fields. Delineation of species boundary, however, can be challenging in a species complex, where different species share a similar morphology and diagnostic characters may not be available. In this context, integrative approaches that incorporate molecular and morphological data sets and account for speciation history can be helpful to alpha taxonomy. Different approaches to species delimitation based on different assumptions are complementary, and by integrating the results from multiple approaches we can generate a more reliable and objective taxonomic decision. In this study, we applied three molecular approaches to species delimitation and inferred the demographic history based on an isolation with migration model to test a morphologically based taxonomic hypothesis for the <em>Cylindera</em> <em>pseudocylindriformis</em> complex. We discuss the association between genetic divergence and microhabitat specialization, and we further corroborated that <em>C</em>. <em>subtilis</em> sp. nov. is a valid new species by integrating the results from model-based species delimitation and the genealogical divergence index. We argue that genetic endemism can form at a small geographic scale, even in a winged insect-like tiger beetle. Our results also indicated that there may still be undocumented species diversity of Taiwanese <em>Cylindera</em> remaining to be discovered.</p>
High-density genomic data reveal fine-scale population structure and pronounced islands of adaptive divergence in lake whitefish (Coregonus clupeaformis) from Lake Michigan
<p>Understanding patterns of genetic structure and adaptive variation in natural populations is crucial for informing conservation and management. Past genetic research using 11 microsatellite loci identified six genetic stocks of lake whitefish (<em>Coregonus clupeaformis</em>) within Lake Michigan, USA. However, ambiguity in genetic stock assignments suggested those neutral microsatellite markers did not provide adequate power for delineating lake whitefish stocks in this system, prompting calls for a genomics approach to investigate stock structure. Here, we generated a dense genomic dataset to characterize population structure and investigate patterns of neutral and adaptive genetic diversity among lake whitefish populations in Lake Michigan. Using Rapture sequencing, we genotyped 829 individuals collected from 17 baseline populations at 197,588 SNP markers after quality filtering. Although the overall pattern of genetic structure was similar to the previous microsatellite study, our genomic data provided several novel insights. Our results indicated a large genetic break between the northwestern and eastern sides of Lake Michigan, and we found a much greater level of population structure on the eastern side compared to the northwestern side. Collectively, we observed five genomic islands of adaptive divergence on five different chromosomes. Each island displayed a different pattern of population structure, suggesting that combinations of genotypes at these adaptive regions are facilitating local adaptation to spatially heterogenous selection pressures. Additionally, we identified a large linkage disequilibrium block of ~8.5 Mb on chromosome 20 that is suggestive of a putative inversion but with a low frequency of the minor haplotype. Our study provides a comprehensive assessment of population structure and adaptive variation that can help inform management of Lake Michigan's lake whitefish fishery and highlights the utility of incorporating adaptive loci into fisheries management. </p>
Fine-scale subpopulation detection via SNP-based unsupervised method: A case study on the 1000 Genomes Project Resources
<p>Here are the supplementary files to the paper "Fine-scale subpopulation detection via SNP-based unsupervised method:<br> A case study on the 1000 Genomes Project Resources".<br> <br> The repository is organized as:</p> <ol> <li><strong>Supplementary information</strong>: the additional detailed information for the experiments in the paper <ul> <li>Supplementary_information_IPCAPS_Chaichoompu_v1.pdf</li> </ul> </li> <li><strong>Real-life dataset</strong>: the 1000 genome dataset, which is referred to in the paper and is filtered with the parameters explained in the paper. Reference: https://www.internationalgenome.org/ <ul> <li>1000genomes_with_filtering.zip</li> </ul> </li> </ol>
Estimating fine-scale changes in turbulence using the movements of a flapping flier
<p>All animals that operate within the atmospheric boundary layer need to respond to aerial turbulence. Yet little is known about how flying animals do this because evaluating turbulence at fine scales (tens to ~ 300 m) is exceedingly difficult. Recently, data from animal-borne sensors have been used to assess wind and updraft strength, providing a new possibility for sensing the physical environment. We tested whether highly-resolved changes in altitude and body acceleration measured onboard solo-flying pigeons (as model flapping fliers) can be used as qualitative proxies for turbulence. A range of pressure and acceleration proxies performed well when tested against independent turbulence measurements from a tri-axial anemometer mounted onboard an ultralight flying the same route, with stronger turbulence causing increasing vertical displacement. The best proxy for turbulence also varied with estimates of both convective velocity and wind shear. The approximately- linear relationship between most proxies and turbulence levels suggests this approach should be widely applicable, providing insight into how turbulence changes in space and time. Furthermore, pigeons were able to fly in levels of turbulence that were unsafe for the ultralight, paving the way for the study of how freestream turbulence affects the costs and kinematics of animal flight.</p>
Fine-scale Quantification of Absorbed Photosynthetically Active Radiation (APAR) in Plantation Forests with 3D Radiative Transfer Modeling and LiDAR Data
<p>In recent years, LiDAR technology has gained widespread attention for its ability to provide precise 3D vertical structural data for various objects, particularly forests. In our dataset, we utilized LiDAR data to reconstruct intricately detailed three-dimensional representations of specific larch forest landscapes. These detailed forest structural models enable us to drive three-dimensional radiative transfer models, analyze the radiation budget of the forest canopy, and gain valuable insights into fine-scale forest management strategies.</p> <p>This is the research work we conducted by combining the aforementioned 3D forest scenes with the 3D RTM LESS. If you use our data, please cite our article. You can access our publication via DOI: 10.34133/plantphenomics.0166.</p> <p>We welcome researchers interested in a wide range of fields, such as vegetation ecological applications, to communicate with us by combining 3D vegetation modeling.</p> <p><br><br></p>
Data from: Identification of reindeer fine-scale foraging behaviour using tri-axial accelerometer data
<p>Animal behavioural responses to the environment ultimately affect their survival. Monitoring animal fine-scale behaviour may improve understanding of animal functional response to the environment and provide an important indicator of the welfare of both wild and domesticated species. In this study, we illustrate the application of collar-attached acceleration sensors for investigating reindeer fine-scale behaviour. Using data from 19 reindeer, we tested the supervised machine learning algorithms random forests, support vector machines, and hidden Markov models to classify reindeer behaviour into seven classes: grazing, browsing low from shrubs or browsing high from trees, inactivity, walking, trotting, and other behaviours. We implemented leave-one-subject-out cross-validation to assess generalizable results on new individuals. Our main results illustrated that hidden Markov models were able to classify collar-attached accelerometer data into all our pre-defined behaviours of reindeer with reasonable accuracy while random forests and support vector machines were biased towards dominant classes. Random forests using 5-second windows had the highest overall accuracy (85%), while hidden Markov models were able to best predict individual behaviours and handle rare behaviours such as trotting and browsing high. We conclude that hidden Markov models provide a useful tool to remotely monitor reindeer and potentially other large herbivore species behaviour. These methods will allow us to quantify fine-scale behavioural processes in relation to environmental events.</p>
Storm-scale and fine-scale boundary layer structures of tropical cyclones simulated with the WRF-LES framework
<p>The numerical simulations were carried out on the Tianhe Supercomputer, China. The TCBL data used in this study are uploaded here. Due to the large number, the original simulation data are available on request (liuqy@cma.gov.cn or liguangwu@fudan.edu.cn).</p>
Limited seed dispersal shapes fine-scale spatial genetic structure in a Neotropical dioecious large-seeded palm
<p><span>Seed and pollen dispersal contribute to gene flow and shape the genetic patterns of plants over fine spatial scales. We inferred fine-scale spatial genetic structure (FSGS) and estimated realized dispersal distances in Phytelephas aequatorialis, a Neotropical dioecious large-seeded palm. We aimed to explore how seed and pollen dispersal shape this genetic pattern in a focal population. For this purpose, we genotyped 138 seedlings and 99 adults with 20 newly developed microsatellite markers. We tested if rodent-mediated seed dispersal has a stronger influence than insect-mediated pollen dispersal in shaping FSGS. We also tested if pollen dispersal was influenced by the density of male palms around mother palms in order to further explore this ecological process in large-seeded plants. Rodent-mediated dispersal of these large seeds occurred mostly over short distances (mean 34.76 ± 34.06 m) while pollen dispersal distances were two times higher (mean 67.91 ± 38.29 m). The spatial extent of FSGS up to 35 m and the fact that seed dispersal did not increase the distance at which male alleles disperse suggest that spatially limited seed dispersal is the main factor shaping FSGS and contributes only marginally to gene flow within the population. Pollen dispersal distances depended on the density of male palms, decreasing when individuals show a clumped distribution and increasing when they are scattered. Our results show that limited seed dispersal mediated by rodents shapes FSGS in P. aequatorialis, while more extensive pollen dispersal accounts for a larger contribution to gene flow and may maintain high genetic diversity.</span></p>
Distinctive, fine-scale distribution of Eastern Caribbean sperm whale vocal clans reflects island fidelity rather than environmental variables
<p>Environmental variables are often the primary drivers of species' distributions as they define their niche. However, individuals, or groups of individuals, may sometimes adopt a limited range within this larger suitable habitat as a result of social and cultural processes. This is the case for Eastern Caribbean sperm whales. While environmental variables are reasonably successful in describing the general distribution of sperm whales in the region, individuals from different cultural groups have distinct distributions around the Lesser Antilles islands. Using data collected over two years of dedicated surveys in the Eastern Caribbean, we conducted habitat modelling and habitat suitability analyses to investigate the mechanisms responsible for such fine-scale distribution patterns. Vocal clan-specific models were dramatically more successful at predicting distribution than general species models, showing how a failure to incorporate social factors can impede accurate predictions. Habitat variation between islands did not explain vocal clan distributions, suggesting that cultural group segregation in the Eastern Caribbean sperm whale is driven by traditions of site/island fidelity (most likely maintained through conformism and homophily) rather than habitat type specialization. Our results provide evidence for the key role of cultural knowledge in shaping habitat use of sperm whales within suitable environmental conditions and highlight the importance of cultural factors in shaping sperm whale ecology. We recommend that social and cultural information be incorporated into conservation and management as culture can segregate populations on fine spatial scales in the absence of environmental variability.</p>
Fine-scale temporal dynamics of flower visitors sheds light on the pollination strategy of a dioecious palm in the Ecuadorian Andes
<p>Background: Dioecious plants generally display sexual dimorphism in male and female floral traits, potentially attracting slightly different pollinator communities. The sharing of common floral visitors between male and female flowers and their timing of visits to both sexes is of critical importance to ensure plant's reproductive success. Palm inflorescences are visited by abundant and diverse insect communities, yet the temporal patterns of insect visits on both sexes remain poorly known.</p> <p>Results: We report 59 morphospecies in the arthropod community, dominated by three beetle families: Staphylinidae, Nitidulidae and Curculionidae. Male inflorescences were more abundantly visited than female, but visitors of the later were taxonomically more diverse. Among the 16 pollinator candidates identified, 9 visited both inflorescence sexes synchronously at dusk /night whereas the others did so asynchronously during the day.</p> <p>Conclusion: Our study provides new insights into the pollination mechanism of P. aequatorialis. We found evidence of differential pollinator attraction between floral sexes, which may be explained by the sexual dimorphism of both flowers. Synchronicity in dusk/night visits of both inflorescence sexes suggests a sexual synchronization of the signal used to attract pollinators.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.